def test_labels(self):
x = np.arange(12).reshape((4, 3))
y = np.arange(8).reshape((4, 2))
ga = GaussianAugmentation()
new_x, new_y = ga(x, y)
self.assertTrue(new_x.shape[0] == new_y.shape[0] == 8)
self.assertTrue(new_x.shape[1:] == x.shape[1:])
self.assertTrue(new_y.shape[1:] == y.shape[1:])
def test_labels(self):
x = np.arange(12).reshape((4, 3))
y = np.arange(8).reshape((4, 2))
ga = GaussianAugmentation()
x_new, new_y = ga(x, y)
self.assertTrue(x_new.shape[0] == new_y.shape[0] == 8)
self.assertEqual(x_new.shape[1:], x.shape[1:])
self.assertEqual(new_y.shape[1:], y.shape[1:])
def test_failure_augmentation_fit_predict(self):
# Assert that value error is raised
with self.assertRaises(ValueError) as context:
_ = GaussianAugmentation(augmentation=True,
apply_fit=True,
apply_predict=True)
self.assertTrue(
'If `augmentation` is `True`, then `apply_fit` must be `True` and `apply_predict`'
' must be `False`.' in str(context.exception))
if __name__ == '__main__':
unittest.main()
def test_no_augmentation(self):
x = np.arange(12).reshape((4, 3))
ga = GaussianAugmentation(augmentation=False)
new_x, _ = ga(x)
self.assertTrue(x.shape == new_x.shape)
self.assertFalse((x == new_x).all())
def test_multiple_size(self):
x = np.arange(12).reshape((4, 3))
ga = GaussianAugmentation(ratio=3.5)
new_x, _ = ga(x)
self.assertTrue(int(4.5 * x.shape[0]) == new_x.shape[0])
def test_double_size(self):
x = np.arange(12).reshape((4, 3))
ga = GaussianAugmentation()
new_x, _ = ga(x)
self.assertTrue(new_x.shape[0] == 2 * x.shape[0])
def test_small_size(self):
x = np.arange(15).reshape((5, 3))
ga = GaussianAugmentation(ratio=0.4)
new_x, _ = ga(x)
self.assertTrue(new_x.shape == (7, 3))
def test_no_augmentation(self):
x = np.arange(12).reshape((4, 3))
ga = GaussianAugmentation(augmentation=False)
x_new, _ = ga(x)
self.assertEqual(x.shape, x_new.shape)
self.assertFalse((x == x_new).all())
def test_multiple_size(self):
x = np.arange(12).reshape((4, 3))
ga = GaussianAugmentation(ratio=3.5)
x_new, _ = ga(x)
self.assertEqual(int(4.5 * x.shape[0]), x_new.shape[0])
def test_double_size(self):
x = np.arange(12).reshape((4, 3))
ga = GaussianAugmentation()
x_new, _ = ga(x)
self.assertEqual(x_new.shape[0], 2 * x.shape[0])
def test_small_size(self):
x = np.arange(15).reshape((5, 3))
ga = GaussianAugmentation(ratio=0.4)
x_new, _ = ga(x)
self.assertEqual(x_new.shape, (7, 3))